Factors Affecting Digital Marketing Adoption in Pakistani Small and Medium Enterprises
Abstract
:1. Introduction
2. Literature Review
2.1. Digital Marketing
2.2. Digital Marketing in SMEs
2.3. Major New Technology Acceptance Models
2.3.1. Innovation Diffusion
2.3.2. The Technology Acceptance Model
2.3.3. Technology Organization Environment
2.3.4. TOE as the Theoretical Lens of the Study
2.4. Factors Affecting Digital Marketing Adoption by SMEs
2.4.1. The Perceived Relative Advantage of Digital Marketing
2.4.2. Perceived Compatibility
2.4.3. Employee Technological Skills
2.4.4. Support of Owners/Managers
2.4.5. Perceived Adoption Cost
2.4.6. Government Policies
2.4.7. Competitive Intensity
2.4.8. Social Influence
2.4.9. Enjoyment with Innovation
2.4.10. Adoption of Digital Marketing and Performance of SMEs
3. Methodology
4. Data Analysis and Results
4.1. Measurement Model Development
4.2. Model Fit Assessment
4.3. Assessment of Measurement Model Reliability and Validity
4.4. Hypotheses Testing
5. Discussion
5.1. Theoretical Contributions
5.2. Practical Contributions
5.3. Limitations and Future Research Directions
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Frequency | Percentage | Valid Percentage | Cumulative Percentage | ||
---|---|---|---|---|---|
Years in business | Less than 1 year | 20 | 5.5 | 5.5 | 5.5 |
1–2 years | 92 | 25.3 | 25.3 | 30.9 | |
2–5 years | 122 | 33.6 | 33.6 | 64.5 | |
More than 5 years | 129 | 35.5 | 35.5 | 100.0 | |
Total | 363 | 100.0 | 100.0 | ||
Type of SME | Manufacturing | 290 | 79.9 | 79.9 | 79.9 |
Services | 73 | 20.1 | 20.1 | 100.0 | |
Total | 363 | 100.0 | 100.0 | ||
Number of employees | Less than 10 | 7 | 1.9 | 1.9 | 1.9 |
10–49 | 97 | 26.7 | 26.7 | 28.7 | |
50–99 | 103 | 28.4 | 28.4 | 57.0 | |
100–249 | 156 | 43.0 | 43.0 | 100.0 | |
Total | 363 | 100.0 | 100.0 | ||
Annual sales | Less than 5 | 94 | 25.9 | 25.9 | 25.9 |
5–10 | 115 | 31.7 | 31.7 | 57.6 | |
More than 10 | 154 | 42.4 | 42.4 | 100.0 | |
Total | 363 | 100.0 | 100.0 | ||
Area of coverage | Local Market | 142 | 39.1 | 39.1 | 39.1 |
National Market | 205 | 56.5 | 56.5 | 95.6 | |
International Market | 16 | 4.4 | 4.4 | 100.0 | |
Total | 363 | 100.0 | 100.0 | ||
Gender of respondent | Male | 316 | 87.1 | 87.1 | 87.1 |
Female | 47 | 12.9 | 12.9 | 100.0 | |
Total | 363 | 100.0 | 100.0 | ||
Ages of respondents | Under 25 years | 228 | 62.8 | 62.8 | 62.8 |
26–35 | 72 | 19.8 | 19.8 | 82.6 | |
36–45 | 36 | 9.9 | 9.9 | 92.6 | |
46–55 | 27 | 7.4 | 7.4 | 100.0 | |
Total | 363 | 100.0 | 100.0 | ||
Qualifications | No formal education | 37 | 10.2 | 10.2 | 10.2 |
High school | 139 | 38.3 | 38.3 | 48.5 | |
College | 122 | 33.6 | 33.6 | 82.1 | |
University | 52 | 14.3 | 14.3 | 96.4 | |
Postgraduate (MS/PhD) | 13 | 3.6 | 3.6 | 100.0 | |
Total | 363 | 100.0 | 100.0 | ||
Experience | Less than 5 | 241 | 66.4 | 66.4 | 66.4 |
6–10 | 91 | 25.1 | 25.1 | 91.5 | |
11–15 | 30 | 8.3 | 8.3 | 99.7 | |
More than 15 | 1 | 0.3 | 0.3 | 100.0 | |
Total | 363 | 100.0 | 100.0 |
N | Min | Max | Mean | Std. Dev. | Skewness | Kurtosis | |||
---|---|---|---|---|---|---|---|---|---|
Std. Error | Std. Error | ||||||||
PRA_DM1 | 363 | 1 | 5 | 3.15 | 1.205 | −0.588 | 0.128 | −0.835 | 0.255 |
PRA_DM2 | 363 | 1 | 5 | 3.17 | 1.259 | −0.431 | 0.128 | −0.934 | 0.255 |
PRA_DM3 | 363 | 1 | 5 | 3.18 | 1.261 | −0.416 | 0.128 | −0.909 | 0.255 |
PRA_DM4 | 363 | 1 | 5 | 3.14 | 1.244 | −0.399 | 0.128 | −0.860 | 0.255 |
PRA_DM5 | 363 | 1 | 5 | 3.35 | 1.297 | −0.433 | 0.128 | −0.998 | 0.255 |
PRA_DM6 | 363 | 1 | 5 | 3.26 | 1.319 | −0.390 | 0.128 | −1.057 | 0.255 |
Comp1 | 363 | 1 | 5 | 3.48 | 1.367 | −0.749 | 0.128 | −0.757 | 0.255 |
Comp2 | 363 | 1 | 5 | 3.60 | 1.289 | −0.714 | 0.128 | −0.709 | 0.255 |
Comp3 | 363 | 1 | 5 | 3.51 | 1.322 | −0.797 | 0.128 | −0.639 | 0.255 |
Comp4 | 363 | 1 | 5 | 3.61 | 1.328 | −0.719 | 0.128 | −0.754 | 0.255 |
PAdp_C1 | 363 | 1 | 5 | 3.61 | 1.269 | −0.835 | 0.128 | −0.298 | 0.255 |
PAdp_C2 | 363 | 1 | 5 | 3.82 | 1.266 | −0.829 | 0.128 | −0.451 | 0.255 |
PAdp_C3 | 363 | 1 | 5 | 3.60 | 1.223 | −0.944 | 0.128 | −0.038 | 0.255 |
EITSkill1 | 363 | 1 | 5 | 3.61 | 1.298 | −0.794 | 0.128 | −0.451 | 0.255 |
EITSkill2 | 363 | 1 | 5 | 3.82 | 1.317 | −0.865 | 0.128 | −0.463 | 0.255 |
EITSkill3 | 363 | 1 | 5 | 3.61 | 1.125 | −0.835 | 0.128 | −0.079 | 0.255 |
Supp_OM1 | 363 | 1 | 5 | 3.45 | 1.392 | −0.573 | 0.128 | −1.002 | 0.255 |
Supp_OM2 | 363 | 1 | 6 | 3.44 | 1.317 | −0.559 | 0.128 | −0.891 | 0.255 |
Supp_OW3 | 363 | 1 | 5 | 3.48 | 1.423 | −0.551 | 0.128 | −1.066 | 0.255 |
Supp_OM4 | 363 | 1 | 5 | 3.36 | 1.354 | −0.617 | 0.128 | −0.918 | 0.255 |
Gov_Pol1 | 363 | 1 | 5 | 3.23 | 1.322 | −0.476 | 0.128 | −0.996 | 0.255 |
Gov_Pol2 | 363 | 1 | 5 | 3.38 | 1.348 | −0.437 | 0.128 | −1.070 | 0.255 |
Gov_Pol3 | 363 | 1 | 5 | 3.19 | 1.276 | −0.476 | 0.128 | −0.926 | 0.255 |
CI1 | 363 | 1 | 5 | 3.52 | 1.332 | −0.651 | 0.128 | −0.880 | 0.255 |
CI2 | 363 | 1 | 5 | 3.64 | 1.331 | −0.792 | 0.128 | −0.583 | 0.255 |
CI3 | 363 | 1 | 5 | 3.66 | 1.265 | −0.682 | 0.128 | −0.615 | 0.255 |
CI4 | 363 | 1 | 5 | 3.69 | 1.236 | −0.683 | 0.128 | −0.566 | 0.255 |
SI1 | 363 | 1 | 5 | 3.50 | 1.288 | −0.632 | 0.128 | −0.848 | 0.255 |
SI2 | 363 | 1 | 5 | 3.41 | 1.336 | −0.544 | 0.128 | −0.906 | 0.255 |
SI3 | 363 | 1 | 5 | 3.50 | 1.297 | −0.586 | 0.128 | −0.851 | 0.255 |
EI1 | 363 | 1 | 5 | 3.72 | 1.274 | −0.945 | 0.128 | −0.284 | 0.255 |
EI2 | 363 | 1 | 5 | 3.55 | 1.342 | −0.506 | 0.128 | −1.033 | 0.255 |
EI3 | 363 | 1 | 5 | 3.73 | 1.284 | −0.663 | 0.128 | −0.839 | 0.255 |
Info_Inte1 | 363 | 1 | 5 | 3.64 | 1.228 | −0.842 | 0.128 | −0.372 | 0.255 |
Info_Inte2 | 363 | 1 | 5 | 3.75 | 1.332 | −0.767 | 0.128 | −0.656 | 0.255 |
Info_Inte3 | 363 | 1 | 5 | 3.68 | 1.284 | −0.817 | 0.128 | −0.496 | 0.255 |
Per1 | 363 | 1 | 5 | 3.53 | 1.192 | −1.089 | 0.128 | 0.096 | 0.255 |
Per2 | 363 | 1 | 5 | 3.56 | 1.035 | −0.889 | 0.128 | 0.043 | 0.255 |
Per3 | 363 | 1 | 5 | 3.47 | 1.133 | −1.062 | 0.128 | 0.164 | 0.255 |
Per4 | 363 | 1 | 5 | 4.09 | 1.226 | −1.366 | 0.128 | 0.737 | 0.255 |
Per5 | 363 | 1 | 5 | 4.07 | 1.327 | −1.408 | 0.128 | 0.663 | 0.255 |
DM_Adp1 | 363 | 1 | 5 | 3.12 | 1.329 | −0.371 | 0.128 | −1.191 | 0.255 |
DM_Adp2 | 363 | 1 | 5 | 3.15 | 1.330 | −0.209 | 0.128 | −1.242 | 0.255 |
DM_Adp3 | 363 | 1 | 5 | 3.13 | 1.418 | −0.301 | 0.128 | −1.298 | 0.255 |
DM_Adp4 | 363 | 1 | 5 | 3.23 | 1.353 | −0.203 | 0.128 | −1.309 | 0.255 |
DM_Adp5 | 363 | 1 | 5 | 3.26 | 1.456 | −0.264 | 0.128 | −1.370 | 0.255 |
Valid N (list-wise) | 363 |
Independent Variable | Collinearity | |
---|---|---|
Tolerance | VIF | |
MeanPRA_DM | 0.483 | 2.070 |
MeanComp | 0.583 | 1.714 |
MeanPAdp_C | 0.751 | 1.332 |
MeanEITSkill | 0.743 | 1.346 |
MeanSupp_OM | 0.411 | 2.432 |
MeanGov_Pol | 0.531 | 1.885 |
MeanCl | 0.795 | 1.258 |
MeanSl | 0.473 | 2.115 |
MeanEl | 0.741 | 1.350 |
Test | Estimates | |
---|---|---|
KMO | 0.935 | |
Bartlett’s | Approx. Chi-Square | 16,442.062 |
Df | 903 | |
Sig. | 0.000 |
Goodness of Fit Indices | Threshold | Reference |
---|---|---|
Chi-Square (X2) | p < 0.05 | |
(X2/DF) | <5 and >1 | |
RMSEA | <0.08 | |
NFI | >0.90 | |
SRMR | <0.05 | |
CFI | >0.90 | |
GFI | >0.90 |
Items | Std. Estimate | AVE | Composite Reliability |
---|---|---|---|
PRA_DM1 | 0.902 | 0.960 | 0.799 |
PRA_DM2 | 0.907 | ||
PRA_DM3 | 0.905 | ||
PRA_DM4 | 0.894 | ||
PRA_DM5 | 0.873 | ||
PRA_DM6 | 0.882 | ||
Per1 | 0.915 | 0.960 | 0.799 |
Per2 | 0.861 | ||
Per3 | 0.901 | ||
Per4 | 0.791 | ||
Per5 | 0.784 | ||
Comp1 | 0.917 | 0.930 | 0.726 |
Comp2 | 0.899 | ||
Comp3 | 0.943 | ||
Comp4 | 0.909 | ||
CI1 | 0.833 | 0.955 | 0.841 |
CI2 | 0.890 | ||
CI3 | 0.888 | ||
CI4 | 0.887 | ||
Supp_OM1 | 0.889 | 0.929 | 0.765 |
Supp_OM2 | 0.886 | ||
Supp_OW3 | 0.876 | ||
Supp_OM4 | 0.909 | ||
EITSkill1 | 0.846 | 0.939 | 0.792 |
EITSkill2 | 0.904 | ||
EITSkill3 | 0.835 | ||
PAdp_C1 | 0.846 | 0.893 | 0.735 |
PAdp_C2 | 0.902 | ||
PAdp_C3 | 0.810 | ||
EI1 | 0.874 | 0.887 | 0.724 |
EI2 | 0.818 | ||
EI3 | 0.899 | ||
DM_Adp1 | 0.908 | 0.898 | 0.747 |
DM_Adp2 | 0.898 | ||
DM_Adp3 | 0.915 | ||
DM_Adp4 | 0.906 | ||
DM_Adp5 | 0.900 | ||
Gov_Pol1 | 0.942 | 0.958 | 0.819 |
Gov_Pol2 | 0.802 | ||
Gov_Pol3 | 0.929 | ||
SI1 | 0.918 | 0.922 | 0.798 |
SI2 | 0.862 | ||
SI3 | 0.904 |
Hyp. | Paths | Std. Est. | SE | CR | p | Decision |
---|---|---|---|---|---|---|
H1 | DM_Adoption<---Per_Relative_A | 0.252 | 0.048 | 5.869 | *** | Supported |
H2 | DM_Adoption<---Compatibility | 0.187 | 0.037 | 4.875 | *** | Supported |
H3 | DM_Adoption<---Comp_Int | 0.057 | 0.035 | 1.773 | 0.076 | Not Supp. |
H4 | DM_Adoption<---Supp_OM | 0.191 | 0.048 | 3.849 | *** | Supported |
H5 | DM_Adoption<---Emp_IT_Skills | 0.142 | 0.039 | 4.128 | *** | Supported |
H6 | DM_Adoption<---Cost | −0.073 | 0.039 | −2.139 | 0.032 | Supported |
H7 | DM_Adoption<---Enj_Innovation | 0.014 | 0.037 | .393 | 0.695 | Not Supp. |
H8 | DM_Adoption<---Gov_Policy | 0.083 | 0.039 | 2.037 | 0.042 | Supported |
H9 | DM_Adoption<---Social_Influence | 0.204 | 0.047 | 4.447 | *** | Supported |
H10 | Performance<---DM_Adoption | 0.619 | 0.044 | 12.764 | *** | Supported |
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Ullah, I.; Khan, M.; Rakhmonov, D.A.; Bakhritdinovich, K.M.; Jacquemod, J.; Bae, J. Factors Affecting Digital Marketing Adoption in Pakistani Small and Medium Enterprises. Logistics 2023, 7, 41. https://doi.org/10.3390/logistics7030041
Ullah I, Khan M, Rakhmonov DA, Bakhritdinovich KM, Jacquemod J, Bae J. Factors Affecting Digital Marketing Adoption in Pakistani Small and Medium Enterprises. Logistics. 2023; 7(3):41. https://doi.org/10.3390/logistics7030041
Chicago/Turabian StyleUllah, Ihsan, Muhammad Khan, Dilshodjon Alidjonovich Rakhmonov, Kalonov Mukhiddin Bakhritdinovich, Julija Jacquemod, and Junghan Bae. 2023. "Factors Affecting Digital Marketing Adoption in Pakistani Small and Medium Enterprises" Logistics 7, no. 3: 41. https://doi.org/10.3390/logistics7030041
APA StyleUllah, I., Khan, M., Rakhmonov, D. A., Bakhritdinovich, K. M., Jacquemod, J., & Bae, J. (2023). Factors Affecting Digital Marketing Adoption in Pakistani Small and Medium Enterprises. Logistics, 7(3), 41. https://doi.org/10.3390/logistics7030041